This research will develop an inexpensive, reliable and portable multichannel electronic system for on-line (real-time speed) and off-line (faster than real-time speed) automatic detection of cortex-derived epileptogenic spikes from multichannel human scalp EEG data. This automatic spike detector will be of a hybrid nature and will not employ or necessarily be part of a general-purpose digital computer. Recent advances in analog and digital integrated electronic circuits as well as in microprocessor technology will be utilized. The system will mimic the human visual pattern recognition process which relies on slope, sharpness, amplitude and duration measurements of the EEG waves and correlates the appearance of the particular wave in question among different EEG channels to separate artifact from cortical activity. It will be able to quantify electrographic characteristics of the cortex-derived spike which are difficult to be effectively analyzed visually from the paper EEG record. The system will be tested in a clinical environment for agreement with the clinical reader and for its capability to eliminate false positives resulting from artifacts or sharp but otherwise normal EEG activity. The system will be also used in various clinical studies to quantify patterns in spike occurrence and/or spike characteristics.